Xiaoqing: A Q&A model for glaucoma based on LLMs.

Glaucoma is one of the leading cause of blindness worldwide. Individuals affected by glaucoma, including patients and their family members, frequently encounter a deficit in dependable support beyond the confines of clinical environments. Seeking advice via the internet can be a difficult task due to the vast amount of disorganized and unstructured material available on these sites, nevertheless.

Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning.

Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemodynamics and cardiac function, and is an effective method for atrial septal defect (ASD) examination. This paper aims to study a deep learning method based on cardiac ultrasound video to assist in ASD diagnosis. We chose four standard views in pediatric cardiac ultrasound to identify atrial septal defects; the four standard views were as follows: subcostal sagittal view of the atrium septum (subSAS), apical four-chamber view (A4C), the low parasternal four-chamber view (LPS4C), and parasternal short-axis view of large artery (PSAX).

Auxiliary Diagnosis of Papillary Thyroid Carcinoma Based on Spectral Phenotype.

Thyroid cancer, a common endocrine malignancy, is one of the leading death causes among endocrine tumors. The diagnosis of pathological section analysis suffers from diagnostic delay and cumbersome operating procedures. Therefore, we intend to construct the models based on spectral data that can be potentially used for rapid intraoperative papillary thyroid carcinoma (PTC) diagnosis and characterize PTC characteristics.

GNAQ R183Q somatic mutation contributes to aberrant arteriovenous specification in Sturge-Weber syndrome through Notch signaling.

Episcleral vasculature malformation is a significant feature of Sturge-Weber syndrome (SWS) secondary glaucoma, the density and diameter of which are correlated with increased intraocular pressure. We previously reported that the GNAQ R183Q somatic mutation was located in the SWS episclera. However, the mechanism by which GNAQ R183Q leads to episcleral vascular malformation remains poorly understood.

Steganography for medical record image.

Medical record images in EHR system are users' privacy and an asset, and there is an urgent need to protect this data. Image steganography can offer a potential solution. A steganographic model for medical record images is therefore developed based on StegaStamp.

Blind Image Quality Assessment for Pathological Microscopic Image Under Screen and Immersion Scenarios.

The high-quality pathological microscopic images are essential for physicians or pathologists to make a correct diagnosis. Image quality assessment (IQA) can quantify the visual distortion degree of images and guide the imaging system to improve image quality, thus raising the quality of pathological microscopic images. Current IQA methods are not ideal for pathological microscopy images due to their specificity.

LightR-YOLOv5: A compact rotating detector for SARS-CoV-2 antigen-detection rapid diagnostic test results.

Nucleic acid testing is currently the golden reference for coronaviruses (SARS-CoV-2) detection, while the SARS-CoV-2 antigen-detection rapid diagnostic tests (RDT) is an important adjunct. RDT can be widely used in the community or regional screening management as self-test tools and may need to be verified by healthcare authorities. However, manual verification of RDT results is a time-consuming task, and existing object detection algorithms usually suffer from high model complexity and computational effort, making them difficult to deploy.

Soluble Solids Content Binary Classification of Miyagawa Satsuma in Chongming Island Based on Near Infrared Spectroscopy.

Citrus is one of the most important fruits in China. Miyagawa Satsuma, one kind of citrus, is a nutritious agricultural product with regional characteristics of Chongming Island. Near-infrared Spectroscopy (NIR) is a proper method for studying the quality of fruits, because it is low-cost, efficient, non-destructive, and repeatable.

Diagnosis of cholangiocarcinoma from microscopic hyperspectral pathological dataset by deep convolution neural networks.

This paper focuses on automatic Cholangiocarcinoma (CC) diagnosis from microscopic hyperspectral (HSI) pathological dataset with deep learning method. The first benchmark based on the microscopic hyperspectral pathological images is set up. Particularly, 880 scenes of multidimensional hyperspectral Cholangiocarcinoma images are collected and manually labeled each pixel as either tumor or non-tumor for supervised learning.

Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.

As being radiation-free, portable, and capable of repetitive use, ultrasonography is playing an important role in diagnosing and evaluating the COVID-19 Pneumonia (PN) in this epidemic. By virtue of lung ultrasound scores (LUSS), lung ultrasound (LUS) was used to estimate the excessive lung fluid that is an important clinical manifestation of COVID-19 PN, with high sensitivity and specificity. However, as a qualitative method, LUSS suffered from large interobserver variations and requirement for experienced clinicians.

Face Mask Assistant: Detection of Face Mask Service Stage Based on Mobile Phone.

Coronavirus Disease 2019 (COVID-19) has spread all over the world since it broke out massively in December 2019, which has caused a large loss to the whole world. Both the confirmed cases and death cases have reached a relatively frightening number. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of COVID-19, can be transmitted by small respiratory droplets.

RIHOOP: Robust Invisible Hyperlinks in Offline and Online Photographs.

In the era of multimedia and Internet, the quick response (QR) code helps people obtain information from offline to online quickly. However, the QR code is often limited in many scenarios because of its random and dull appearance. Therefore, this article proposes a novel approach to embed hyperlinks into common images, making the hyperlinks invisible for human eyes but detectable for mobile devices equipped with a camera.

Identification of Melanoma From Hyperspectral Pathology Image Using 3D Convolutional Networks.

Skin biopsy histopathological analysis is one of the primary methods used for pathologists to assess the presence and deterioration of melanoma in clinical. A comprehensive and reliable pathological analysis is the result of correctly segmented melanoma and its interaction with benign tissues, and therefore providing accurate therapy. In this study, we applied the deep convolution network on the hyperspectral pathology images to perform the segmentation of melanoma.

Detection of Respiratory Infections Using RGB-Infrared Sensors on Portable Device.

Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronaviruses 2 (SARS-CoV-2) has become a serious global pandemic in the past few months and caused huge loss to human society worldwide. For such a large-scale pandemic, early detection and isolation of potential virus carriers is essential to curb the spread of the pandemic. Recent studies have shown that one important feature of COVID-19 is the abnormal respiratory status caused by viral infections.

Matrix decomposition for modeling lesion development processes in multiple sclerosis.

Our main goal is to study and quantify the evolution of multiple sclerosis lesions observed longitudinally over many years in multi-sequence structural magnetic resonance imaging (sMRI). To achieve that, we propose a class of functional models for capturing the temporal dynamics and spatial distribution of the voxel-specific intensity trajectories in all sMRI sequences. To accommodate the hierarchical data structure (observations nested within voxels, which are nested within lesions, which, in turn, are nested within study participants), we use structured functional principal component analysis.

Correction: Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples.

[This corrects the article DOI: 10.1371/journal.pone.

Experimental design and sample size considerations in longitudinal magnetic resonance imaging-based biomarker detection for multiple sclerosis.

Several modeling approaches have been developed to quantify differences in multiple sclerosis lesion evolution on magnetic resonance imaging to identify the effect of treatment on disease progression. These studies have limited clinical applicability due to onerous scan frequency and lengthy study duration. Efficient methods are needed to reduce the required sample size, study duration, and sampling frequency in longitudinal magnetic resonance imaging studies.

Estimating Departure Time Using Thermal Camera and Heat Traces Tracking Technique.

Advancement in science and technology is playing an increasingly important role in solving difficult cases at present. Thermal cameras can help the police crack difficult cases by capturing the heat trace on the ground left by perpetrators, which cannot be spotted by the naked eye. Therefore, the purpose of this study is to establish a thermalfoot model using thermal imaging system to estimate the departure time.

Machine learning-guided design and development of multifunctional flexible Ag/poly (amic acid) composites using the differential evolution algorithm.

The development of flexible composites is of great significance in the flexible electronic field. In combination with machine learning technology, the introduction of artificial intelligence to flexible materials design, synthesis, characterization and application research will greatly promote the flexible materials research efficiency. In this study, the back propagation (BP) neural network based on the differential evolution (DE) algorithm was applied to determine the electrical properties of the flexible Ag/poly (amic acid) (PAA) composite structure and to develop flexible materials for its different applications.

Paper-Based ZnS:Cu Alternating Current Electroluminescent Devices for Current Humidity Sensors with High-Linearity and Flexibility.

Humidity sensors are indispensable for various electronic systems and instrumentations. To develop a new humidity sensing mechanism is the key for the next generation of sensor technology. In this work, a novel flexible paper-based current humidity sensor is proposed.

Correction: Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples.

[This corrects the article DOI: 10.1371/journal.pone.

Temporal Trends Associated With the Rise in Alcoholic Liver Disease-related Liver Transplantation in the United States.

Background: In the United States, alcoholic liver disease (ALD) has recently become the leading indication for liver transplantation.

Methods: Using the United Network for Organ Sharing registry, we examined temporal trends in adult liver transplant waitlist (WL) registrants and recipients with chronic liver disease (CLD) due to ALD from 2007 to 2016.

Results: From 2007 to 2016, ALD accounted for 20.

Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples.

In recent years, an increasing number of studies have reported the presence of plant miRNAs in human samples, which resulted in a hypothesis asserting the existence of plant-derived exogenous microRNA (xenomiR). However, this hypothesis is not widely accepted in the scientific community due to possible sample contamination and the small sample size with lack of rigorous statistical analysis. This study provides a systematic statistical test that can validate (or invalidate) the plant-derived xenomiR hypothesis by analyzing 388 small RNA sequencing data from human samples in 11 types of body fluids/tissues.